A survey on algorithmic aspects of modular decomposition

The modular decomposition is a technique that applies but is not restricted to graphs. The notion of module naturally appears in the proofs of many graph theoretical theorems. Computing the modular decomposition tree is an important preprocessing step to solve a large number of combinatorial optimization problems. Since the first polynomial time algorithm in the early 70's, the algorithmic of the modular decomposition has known an important development. This paper survey the ideas and techniques that arose from this line of research

Usefulness of EQ-5D in Assessing Health Status in Primary Care Patients with Major Depressive Disorder

Objectives Major depressive disorder (MDD) is a prevalent psychiatric disorder associated with impaired patient functioning and reductions in health-related quality of life (HRQL). The present study describes the impact of MDD on patients' HRQL and examines preference-based health state differences by patient features and clinical characteristics. Methods 95 French primary care practitioners recruited 250 patients with a DSM-IV diagnosis of MDD for inclusion in an eight-week follow-up cohort. Patient assessments included the Montgomery Asberg Depression Rating Scale (MADRS), the Clinical Global Impression of Severity (CGI), the Short Form-36 Item scale (SF-36), the Quality of Life Depression Scale (QLDS) and the EuroQoL (EQ-5D). Results The mean EQ-5D utility at baseline was 0.33, and 8% of patients rated their health state as worse than death. There were no statistically significant differences in utilities by demographic features. Significant differences were found in mean utilities by level of disease severity assessed by CGI. The different clinical response profiles, assessed by MADRS, were also revealed by EQ-5D at endpoint: 0.85 for responders remitters, 0.72 for responders non-remitter, and 0.58 for non-responders. Even if HRQL and EQ-5D were moderately correlated, they shared only 40% of variance between baseline and endpoint. Conclusions Self-reported patient valuations for depression are important patient-reported outcomes for cost-effectiveness evaluations of new antidepressant compounds and help in further understanding patient compliance with antidepressant treatment

Cloud point extraction of phenol and benzyl alcohol from aqueous stream

Two-aqueous phase extraction of phenol and benzyl alcohol as a solute from their aqueous solutions was investigated using polyethoxylated alcohols (CiEj) as a biodegradable non-ionic surfactant. First, the phase diagrams of the binary systems, water–surfactant (Oxo-C10E3 and Oxo- C13E9), and the pseudo-binary systems, water–surfactant with a constant concentration of solute was determined. The effect of sodium chloride and sodium sulphate on water–surfactant systems were studied. According to the given surfactants concentrations and temperatures, the extraction results were expressed by the following four parameters, percentage of extracted solute, E, which reached 95 and 90% for phenol and benzyl alcohol, respectively, residual concentrations of solute, Xs,w, and the surfactant, Xt,w, in the dilute phase and volume fraction of the coacervate at the equilibrium condition, φc. The values of these parameters were determined by an analyzing central composite designs. After the first extraction process, phenol and benzyl alcohol concentrations in the effluent were reduced about ten times for the first and four times for the second, correspondingly

Heavy Higgs Searches: Flavour Matters

We point out that the stringent lower bounds on the masses of additional electrically neutral and charged Higgs bosons crucially depend on the flavour structure of their Yukawa interactions. We show that these bounds can easily be evaded by the introduction of flavour-changing neutral currents in the Higgs sector. As an illustration, we study the phenomenology of a two Higgs doublet model with a Yukawa texture singling out the third family of quarks and leptons. We combine constraints from low-energy flavour physics measurements, LHC measurements of the 125 GeV Higgs boson rates, and LHC searches for new heavy Higgs bosons. We propose novel LHC searches that could be performed in the coming years to unravel the existence of these new Higgs bosons.Comment: 41 pages, 11 figures and 4 tables (v2: References added. Comment on associated production with a top quark added. Matched published version.

Practical and Efficient Split Decomposition via Graph-Labelled Trees

Split decomposition of graphs was introduced by Cunningham (under the name join decomposition) as a generalization of the modular decomposition. This paper undertakes an investigation into the algorithmic properties of split decomposition. We do so in the context of graph-labelled trees (GLTs), a new combinatorial object designed to simplify its consideration. GLTs are used to derive an incremental characterization of split decomposition, with a simple combinatorial description, and to explore its properties with respect to Lexicographic Breadth-First Search (LBFS). Applying the incremental characterization to an LBFS ordering results in a split decomposition algorithm that runs in time $O(n+m)\alpha(n+m)$, where $\alpha$ is the inverse Ackermann function, whose value is smaller than 4 for any practical graph. Compared to Dahlhaus' linear-time split decomposition algorithm [Dahlhaus'00], which does not rely on an incremental construction, our algorithm is just as fast in all but the asymptotic sense and full implementation details are given in this paper. Also, our algorithm extends to circle graph recognition, whereas no such extension is known for Dahlhaus' algorithm. The companion paper [Gioan et al.] uses our algorithm to derive the first sub-quadratic circle graph recognition algorithm